The lung sounds data analysis USES time domain analysis, frequency domain analysis, power spectra analysis, time-varying spectra analysis and so on.
肺音分析采用了时域分析、功率谱分析、时变谱分析、同态处理等多种分析算法。
The data of polar motion, rotation of the earth and atmospheric excitation function are analysed by the Auto-Regression power spectrum method, and their spectra at low frequency band are obtained.
本文用自回归功率谱方法分析了极移、地球自转和大气激发函数的资料，得到了它们的低频谱。
The Raman and FTIR spectra show that the structure and composition of the films change with the radio-frequency power.
拉曼及傅里叶变换红外光谱分析显示，随着射频功率的改变，薄膜的结构和组分也随之变化。
So the influence of high-frequency noise is analyzed by the analysis of power spectra, coherent structure, probability distribution of time series and differences of them.
针对这些现象，从谱、相干结构、时间序列本身的概率分布和标量差的概率分布，分析了高频噪声的影响。
So the influence of high-frequency noise is analyzed by the analysis of power spectra, coherent structure, probability distribution of time series and differences of them.
针对这些现象，从谱、相干结构、时间序列本身的概率分布和标量差的概率分布，分析了高频噪声的影响。
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